• Conclusion stability for natural language based mining of design discussions 

  Mahadi, Alvi (2021-02-11)

  Developer discussions range from in-person hallway chats to comment chains on bug reports. Being able to identify discussions that touch on software design would be helpful in documentation and refactoring software. Design ...
• On the difficulty of generalizing deep reinforcement learning framework for combinatorial optimization 

  Pashazadeh, Mostafa (2021-01-19)

  Combinatorial optimization problems on the graph with real-life applications are canonical challenges in Computer Science. The difficulty of finding quality labels for problem instances holds back leveraging supervised ...
• Metric learning for multivariate time series analysis using DTW: application to remote sensing and software engineering 

  Salaou, Abdoul-Djawadou (2021-01-19)

  In the context of growing availability of data, Time Series are essential for extracting and understanding the evolution of underlying natural, artificial, social or economic phenomena. The related literature has extensively ...
• New approaches to improving live video delivery over content delivery networks 

  Wang, Huan (2021-01-05)

  The live streaming services have gained extreme popularity in recent years. The spiky traffic, as well as the real-time property of live videos, make it challenging for content delivery networks (CDNs) to guarantee the ...
• Taxonomies of software ecosystem health metrics and practices: a systematic literature review 

  Yousef Zadeh Shooshtari, Arman (2020-12-21)

  Context: Since the beginnings of software engineering, metrics (such as SLOCs) and practices have been used in an attempt to measure and improve the features of software development projects, their process, or their ...
• Privacy preserving software engineering for data driven development 

  Tongay, Karan Naresh (2020-12-14)

  The exponential rise in the generation of data has introduced many new areas of research including data science, data engineering, machine learning, artificial in- telligence to name a few. It has become important for any ...
• Fast and scalable triangle counting in graph streams: the hybrid approach 

  Singh, Paramvir (2020-12-14)

  Triangle counting is a major graph problem with several applications in social network analysis, anomaly detection, etc. A considerable amount of work has contributed to approximately computing the global triangle counts ...
• U-Net ship detection in satellite optical imagery 

  Smith, Benjamin (2020-10-05)

  Deep learning ship detection in satellite optical imagery suffers from false positive occurrences with clouds, landmasses, and man-made objects that interfere with correctly classifying ships. A custom U-Net is implemented ...
• An evaluation of deep learning semantic segmentation for land cover classification of oblique ground-based photography 

  Rose, Spencer (2020-09-30)

  This thesis presents a case study on the application of deep learning methods for the dense prediction of land cover types in oblique ground-based photography. While deep learning approaches are widely used in land cover ...
• Code duplication and reuse in Jupyter notebooks 

  Koenzen, Andreas Peter (2020-09-21)

  Reusing code can expedite software creation, analysis and exploration of data. Expediency can be particularly valuable for users of computational notebooks, where duplication allows them to quickly test hypotheses and ...
• Concentrated network tomography and bound-based network tomography 

  Feng, Cuiying (2020-09-17)

  Modern computer networks pose a great challenge for monitoring the network performance due to their large scale and high complexity. Directly measuring the performance of internal network elements is prohibitive due to ...
• BUDI: Building Urban Designs Interactively - a spatial-based visualization and collaboration platform for urban design 

  Sun, Xi (2020-09-03)

  BUDI (Building Urban Designs Interactively) is an integrated 3D visualization and remote collaboration platform for complex urban design tasks. Users with different backgrounds can remotely engage in the entire design ...
• Exploring fair machine learning in sequential prediction and supervised learning 

  Azami, Sajjad (2020-09-02)

  Algorithms that are being used in sensitive contexts such as deciding to give a job offer or giving inmates parole should be accurate as well as being non-discriminatory. The latter is important especially due to emerging ...
• Autonomic test case generation of failing code using AOP 

  Murguia, Giovanni (2020-09-02)

  As software systems have grown in size and complexity, the costs of maintaining such systems increases steadily. In the early 2000's, IBM launched the autonomic computing initiative to mitigate this problem by injecting ...
• Thompson sampling-based online decision making in network routing 

  Huang, Zhiming (2020-09-02)

  Online decision making is a kind of machine learning problems where decisions are made in a sequential manner so as to accumulate as many rewards as possible. Typical examples include multi-armed bandit (MAB) problems ...
• Active learning under the Bernstein condition for general losses 

  Shayestehmanesh, Hamid (2020-08-31)

  We study online active learning under the Bernstein condition for bounded general losses and offer a solution for online variance estimation. Our suggested algorithm is based on IWAL (Importance Weighted Active Learning) ...
• Marine visualization system: an augmented reality approach 

  Cojoc-Wisernig, Eduard (2020-08-28)

  Sailboat operation must account for a variety of environmental factors, including wind, tidal currents, shore features and atmospheric conditions. We introduce the first method of rendering an augmented reality scene for ...
• Improvement and partial simulation of King & Saia’s expected-polynomial-time Byzantine agreement algorithm 

  Kimmett, Ben (2020-06-16)

  We present a partial implementation of King and Saia 2016’s expected polyno- mial time byzantine agreement algorithm, which which greatly speeds up Bracha’s Byzantine agreement algorithm by introducing a shared coin flip ...
• Tradeoffs and challenges in maintaining location privacy in location-based services 

  Alzahrani, Thuraya (2020-05-27)

  Protecting location privacy in digital services could not be more important. This research aims to protect the location of people who suffer from opioid overdose while seeking help from public, emergency services and ...
• Preserving large cuts in fully dynamic graphs 

  Wasim, Omer (2020-05-21)

  This thesis initiates the study of the MAX-CUT problem in fully dynamic graphs. Given a graph $G=(V,E)$, we present the first fully dynamic algorithms to maintain a $\frac{1}{2}$-approximate cut in sublinear update time ...

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